Recent advances in the potential of modeling and simulation to assess the performance of modified atmosphere packaging (MAP) systems for the fresh agricultural product: Challenges and development

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BackgroundThe metabolic process and physiological activities of fresh fruit and vegetables continue after harvesting and lead to quality reduction and waste enhancement. Modified atmosphere packaging (MAP) is a well-proven method to avoid anaerobiosis activities and extend the shelf life of agricultural products. As a result, researchers have proposed MAP technology as an appropriate and cost-effective method. The design of MAP systems depends on various factors, including the respiration and transpiration rates of the product, the temperature and humidity of the environment, and the permeability rate of the package. Therefore, the integration of mentioned information in the design of a successful MAP system is crucial. Scope and approachThe modeling approach is a reliable method for understanding the incorporation of the effective parameters and achieving the mass balance equation to determine the optimal conditions of the MAP. This review investigates the developed models for achieving a MAP design for various agricultural products. Also, the existing challenges in the developed models are discussed. In addition, the strengths and shortcomings of the integrated models are described, and the prospects for the optimization of MAP are highlighted. Key findings and conclusionsConsidering the interaction of effectual parameters and sub-models, mathematical modeling revealed acceptable accuracy to predict the shelf life of fresh produce under the actual supply chain conditions and MAP systems. Due to the difference in the optimum MAP requirements based on specific parameters such as gas concentration, research is needed to optimize the effective factors by taking into account the perm-selectivity of the packaging materials. More efforts should focus on developing the comprehensive mathematical model and simulation, including product characteristics, package properties, environmental conditions, and mass and heat transfer phenomena for optimal MAP design.